1. Field of the Invention
The present invention is directed generally to technology for identifying remote computing devices through network communications. More specifically, the invention is directed to identifying an active user of a remote computing device by detecting a combination of device element data and user behavioral data to differentiate among multiple users of a common device.
2. Description of the Related Art
The science of determining consumer values, likes, and dislikes through the prism of human interaction with technology has modern roots in ratings systems developed for measuring the response of mass population to television broadcasting. Advertisers and broadcasters have customarily relied on ratings systems such as the Nielsen system to determine viewership or audience size, i.e. an estimate of the total population of viewers tuned in to a particular TV program, so that the value of advertising slots broadcast during the program can be fairly assessed. The Nielsen system in its earliest application relied on written diaries kept and submitted by a sampling of consumers. Statistics gathered by this system are of questionable reliability, as the accuracy depends on the truth and diligence of consumers lazily engaged in the leisure activity of watching television.
Until recently, video entertainment for the consumer at large has been broadcast almost exclusively for reception on conventional television sets. Advancements in computers and compression technologies have now made it possible for consumers to receive much of the same entertainment as streaming video on a computer monitor or a hand-held computing device such as a smart phone or an Apple® iPod®. The computing devices enable consumers to interact with the broadcasting experience, by providing the consumer with an abundance of programming selections from an ever increasing number of entertainment-providing sites accessible via the world-wide web. Today, consumers on the go who prefer to stream video entertainment into their mobile devices are even less likely to make meaningful diary entries.
In a later application of the Nielsen system, set meters were developed in an effort to eliminate inaccuracies introduced by human data collection. Set meters are electronic devices that monitor which station the television displays at a given sampling time, and transmit the information to a central database using telephone lines. Set meters, however, introduce other sources of inaccuracy. For example, a set meter can erroneously report viewership habits when a TV is left on when no one is home or when everyone in the house has fallen asleep. Set meter technology has not kept pace with advances in TV technology, which have in recent years introduced new digital broadcasting standards and a proliferation of manufacturers and models that create compatibility problems.
The Nielsen diary and set meter methods for collecting viewership data have been made even more impractical with the advent of streaming video that is deliverable directly to a personal or laptop computer or mobile computing device. Consumers may now watch video programs, or portions of programs, while working on a PC, while traveling, or wherever they may be. The many types of computing devices available to the consumer that are capable of receiving streaming video have rendered set meter technology inadequate for effective viewership capture. There is now more interest than ever in collecting viewership data that not only indicates whether a program is being watched, but also the types of devices that are receiving it. What is needed is a reliable system for collecting viewership data for video entertainment that is delivered to a wide variety of computing devices.